scholarly journals Author Productivity of COVID-19 Research Output Globally: Testing Lotka's Law

2020 ◽  
Author(s):  
Kutty Kumar
Keyword(s):  
Research Output ◽  
Author Productivity ◽  
Lotka’S Law

scholarly journals Assessment of the NIH-supported relative citation ratio as a measure of research productivity among 1687 academic neurological surgeons

2020 ◽  
pp. 1-8
Author(s):  
Vamsi Reddy ◽  
Arjun Gupta ◽  
Michael D. White ◽  
Raghav Gupta ◽  
Prateek Agarwal ◽  
...  
Keyword(s):  
Research Productivity ◽  
Research Output ◽  
Academic Rank ◽  
H Index ◽  
Relative Citation ◽  
Retrospective Data Analysis ◽  
Author Productivity ◽  
Doctor Of Philosophy ◽  
Male Sex ◽  
Number Of Citations

OBJECTIVEPublication metrics such as the Hirsch index (h-index) are often used to evaluate and compare research productivity in academia. The h-index is not a field-normalized statistic and can therefore be dependent on overall rates of publication and citation within specific fields. Thus, a metric that adjusts for this while measuring individual contributions would be preferable. The National Institutes of Health (NIH) has developed a new, field-normalized, article-level metric called the “relative citation ratio” (RCR) that can be used to more accurately compare author productivity between fields. The mean RCR is calculated as the total number of citations per year of a publication divided by the average field-specific citations per year, whereas the weighted RCR is the sum of all article-level RCR scores over an author’s career. The present study was performed to determine how various factors, such as academic rank, career duration, a Doctor of Philosophy (PhD) degree, and sex, impact the RCR to analyze research productivity among academic neurosurgeons.METHODSA retrospective data analysis was performed using the iCite database. All physician faculty affiliated with Accreditation Council for Graduate Medical Education (ACGME)–accredited neurological surgery programs were eligible for analysis. Sex, career duration, academic rank, additional degrees, total publications, mean RCR, and weighted RCR were collected for each individual. Mean RCR and weighted RCR were compared between variables to assess patterns of analysis by using SAS software version 9.4.RESULTSA total of 1687 neurosurgery faculty members from 125 institutions were included in the analysis. Advanced academic rank, longer career duration, and PhD acquisition were all associated with increased mean and weighted RCRs. Male sex was associated with having an increased weighted RCR but not an increased mean RCR score. Overall, neurological surgeons were highly productive, with a median RCR of 1.37 (IQR 0.93–1.97) and a median weighted RCR of 28.56 (IQR 7.99–85.65).CONCLUSIONSThe RCR and its derivatives are new metrics that help fill in the gaps of other indices for research output. Here, the authors found that advanced academic rank, longer career duration, and PhD acquisition were all associated with increased mean and weighted RCRs. Male sex was associated with having an increased weighted, but not mean, RCR score, most likely because of historically unequal opportunities for women within the field. Furthermore, the data showed that current academic neurosurgeons are exceptionally productive compared to both physicians in other specialties and the general scientific community.

Collaboration and author productivity: A study with a new variable in Lotka's law

1999 ◽  
Vol 44 (1) ◽  
pp. 129-134 ◽  
Author(s):  
B. M. Gupta ◽  
C. R. Karisiddippa
Keyword(s):  
Author Productivity ◽  
Lotka’S Law

Bibliometric study of social network analysis literature

2019 ◽  
Vol 38 (2) ◽  
pp. 420-433 ◽  
Author(s):  
Yu-Sheng Su ◽  
Chien-Linag Lin ◽  
Shih-Yeh Chen ◽  
Chin-Feng Lai
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Bibliometric Analysis ◽  
Computer Mediated Communication ◽  
Content Type ◽  
Productivity Distribution ◽  
Author Productivity ◽  
Subject Areas ◽  
Lotka’S Law

Purpose The purpose of this paper is to use bibliometric analysis to identify the current state of the academic literature regarding social network analysis (SNA) and analyze its knowledge base such as research authors, research countries, document type, keyword analysis and subject areas. Design/methodology/approach Bibliometric analysis is used and furthermore, Lotka’s and Bradford’s law is applied to perform author productivity analyses in this field during 1999 and 2018, respectively, in turn, discovering historical vein and research tendency in the future. Findings It appears that the research on SNA has been very popular and still in the highly mature period. So far, the USA takes the lead among the published paper. The top 2 subject areas are “Computer Science” and “Business Economics.” The primary journal that SNA articles were published is Computers in Human Behavior. SNA has been related to many research areas, such as “Social network analysis,” “Computer-mediated communication,” “Online learning,” “Social Network” and “Community of inquiry.” Finally, Kolmogorov–Smirnov (K-S) test proved that the frequency indexes of author productivity distribution certainly followed Lotka’s law. Research limitations/implications First, the productivity distribution may inform researchers and scholars of current issues and development of SNA. Second, the study proposed a theoretical model, based on Lotka’s law, for author productivity analysis of SNA, which can serve as reference for different areas of study in the evaluation of author productivity models. Also, in order to allow researchers to gain in-depth insights, this study aimed to report the most published institutions and keep track of the growth and trend of author productivity, by which scholars in related fields are provided with more opportunities for academic communication and technological cooperation. Originality/value This research on the productivity distribution of SNA may inform researchers and scholars of current issues and development of SNA. The findings report the major publication outlets and related discussion issues about SNA. Such information would be valuable for related authors, who are writing the manuscript on SNA, and also for practitioners, who may be interested in applying the theory or ideas of SNA.

Humanitarian Logistics

2018 ◽  
Vol 11 (4) ◽  
pp. 53-71 ◽  
Author(s):  
Anil Kumar ◽  
G.S. Kushwaha
Keyword(s):  
Research Impact ◽  
Humanitarian Logistics ◽  
Distribution Data ◽  
Scientometric Analysis ◽  
Authorship Pattern ◽  
Publication Patterns ◽  
Major Subject ◽  
Author Productivity ◽  
Subject Areas ◽  
Lotka’S Law

The concept of humanitarian logistics is evolving rapidly and gaining popularity in the research community. This research reviews the literature on humanitarian logistics for providing a thorough outlook into the field. In this study, Authors conducted a scientometric analysis of the literature published in 1998–2015 to empirically explore the important areas and key contributors of humanitarian logistics research and providing new outlook towards publication patterns, authorship pattern, major subject areas, research impact, and research productivity. By using scientometric analysis, the research critically evaluates 509 articles published over the past 18 years and identifies some of the major contributing authors, organizations and key research topics related to the field. In the last, the paper examines the validity of Lotka's law to authorship pattern in humanitarian logistics. The result found that the author productivity distribution data in humanitarian logistics do not follow Lotka's law. The findings of the study provide a new outlook on humanitarian logistics research.

scholarly journals Produktivitas Pengarang Menggunakan Hukum Lotka Dengan Teknik Complete Count Pada Jurnal Kedokteran YARSI Tahun 2009-2018

2020 ◽  
Vol 1 (1) ◽  
pp. 1-12
Author(s):  
Danang Dwijo Kangko ◽  
Rahmadhani Rahmadhani ◽  
Elfitri Kurnia Erza
Keyword(s):  
Medical Journal ◽  
Journal Article ◽  
Science Research ◽  
Analysis Data ◽  
Critical Value ◽  
Maximum Deviation ◽  
Author Productivity ◽  
Lotka’S Law ◽  
Complete Count ◽  
Productivity Pattern

Researchers research to develop science. Research results are published as a form of scientific communication. One type of scientific publication is a journal article. YARSI Medical Journal is a peer-reviewed journal in the field of medicine and health that is open to the public owned by YARSI University. The author's productivity patterns in the YARSI Medical Journal so far are unknown. Author productivity is the number of papers produced by the author on a particular subject and published in scientific journals in a certain period. This study aims to (1) Determine the author's productivity patterns using Lotka's Law with complete count techniques in YARSI Medical Journal 2009-2018; (2) Testing the suitability of the frequency of Lotka's Law with the author's frequency distribution using the complete count technique in YARSI Medical Journal 2009-2018. The research method used in this study is a quantitative method with bibliometric analysis. Data collection uses documentation method. The results of this study include (1) the pattern of author productivity with an exponent value (n) 2.874110535 and the constant (C) 0.820080499 meaning that the author contributing to one article is 82.00% of the total number of authors, it can be said that the YARSI Medical Journal Author Productivity Pattern 2009- 2018 is low or less productive. (2) Based on the K-S test the maximum deviation is 0 and the critical value is 0.0829206. Dmax is smaller than the critical value, so H0 is accepted. That is, the Author Productivity Pattern uses the Complete Count Technique in YARSI Medical Journal 2009-2018 following Lotka's Law.

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